859 resultados para conditional expected utility


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IMAC can be used to selectively enrich phosphopeptides from complex peptide mixtures, but co-retention of acidic peptides together with the failure to retain some phosphopeptides restricts the general utility of the method. In this study Fe(III)-IMAC was qualitatively and quantitatively assessed using a panel of phosphopeptides, both synthetic and derived from proteolysis of known phosphoproteins, to identify the causes of success and failure in the application of this technique. Here we demonstrate that, as expected, peptides with a more acidic amino acid content are generally more efficiently purified and detected by MALDI-MS after Fe(III)-IMAC than those with a more basic content. Modulating the loading buffer used for Fe(III)-IMAC significantly affects phosphopeptide binding and suggests that conformational factors that lead to steric hindrance and reduced accessibility to the phosphate are important. The use of 1,1,1,3,3,3-hexafluoroisopropanol is shown here to significantly improve Fe(III)-IMAC enrichment and subsequent detection of phosphopeptides by MALDI-MS.

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In previous empirical and modelling studies of rare species and weeds, evidence of fractal behaviour has been found. We propose that weeds in modern agricultural systems may be managed close to critical population dynamic thresholds, below which their rates of increase will be negative and where scale-invariance may be expected as a consequence. We collected detailed spatial data on five contrasting species over a period of three years in a primarily arable field. Counts in 20×20 cm contiguous quadrats, 225,000 in 1998 and 84,375 thereafter, could be re-structured into a wide range of larger quadrat sizes. These were analysed using three methods based on correlation sum, incidence and conditional incidence. We found non-trivial scale invariance for species occurring at low mean densities and where they were strongly aggregated. The fact that the scale-invariance was not found for widespread species occurring at higher densities suggests that the scaling in agricultural weed populations may, indeed, be related to critical phenomena.

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IMAC can be used to selectively enrich phosphopeptides from complex peptide mixtures, but co-retention of acidic peptides together with the failure to retain some phosphopeptides restricts the general utility of the method. In this study Fe(III)-IMAC was qualitatively and quantitatively assessed using a panel of phosphopeptides, both synthetic and derived from proteolysis of known phosphoproteins, to identify the causes of success and failure in the application of this technique. Here we demonstrate that, as expected, peptides with a more acidic amino acid content are generally more efficiently purified and detected by MALDI-MS after Fe(III)-IMAC than those with a more basic content. Modulating the loading buffer used for Fe(III)-IMAC significantly affects phosphopeptide binding and suggests that conformational factors that lead to steric hindrance and reduced accessibility to the phosphate are important. The use of 1,1,1,3,3,3-hexa-fluoroisopropanol is shown here to significantly improve Fe(III)-IMAC enrichment and subsequent detection of phosphopeptides by MALDI-MS.

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Wind catcher systems have been employed in buildings in the Middle East for many centuries and they are known by different names in different parts of the region. Recently there has been an increase in the application of this approach for natural ventilation and passive cooling in the UK and other countries. This paper presents the results of experimental wind tunnel and smoke visualisation testing, combined with CFD modelling, to investigate the performance of the wind catcher. For this purpose, a full-scale commercial system was connected to a test room and positioned centrally in an open boundary wind tunnel. Because much ventilation design involves the use of computational fluid dynamics, the measured performance of the system was also compared against the results of CFD analysis. Configurations included both a heated and unheated space to determine the impact of internal heat sources on airflow rate. Good comparisons between measurement and CFD analysis were obtained. Measurements showed that sufficient air change could be achieved to meet both air quality needs and passive cooling.

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Innovation continues to be high on the agenda in construction. It is widely considered to be an essential prerequisite of improved performance both for the sector at large and for individual firms. Success stories dominate the parts of the academic literature that rely heavily on the recollections of key individuals. A complementary interpretation focuses on the way innovation champions in hindsight interpret, justify and legitimize the diffusion of innovations. Emphasis is put on the temporal dimension of interpretation and how this links to rhetorical strategies and impression management tactics. Rhetorical theories are drawn upon to analyse the accounts given by innovation champions in seven facilities management organizations. In particular, the three persuasive appeals in classic rhetoric are used to highlight the rhetorical justifications mobilized in the descriptions of what took place. The findings demonstrate the usefulness of rhetorical theories in complementing studies of innovation.

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A flavonoid survey was carried out on 45 taxa from the genera Shorea, Hopea, Parashorea, Neobalanocarpus, and Dryobalanops of the tribe Shoreae in the Dipterocarpaceae. The study showed significant chemotaxonomic differences in leaf flavonoid aglycone patterns and the presence of tannins in these taxa. The flavonoid patterns are useful in the delimitation of some taxa. For example, the genus Parashorea is distinguished by the universal presence of kaempferol 3-methyl ether, and the monotypic genus Neobalanocarpus is unique in not producing ellagic and gallo tannins. The presence of chalcones and flavone C-glycosides supports the separation of the genus Hopea into two sections, section Dryobalanoides and section Hopea in Ashton's classification, which is based on the type of venation. The flavonoid distributions in this study show that they can be very useful for differentiating between the Balau group in the genus Shorea, and some scaly barked Hopea species, particularly H. helferi (lintah bukit), H. nutans (giam), and H. ferrea (malut). (C) 2008 The Linnean Society of London.

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Initial bacterial colonization, including colonization with health-positive bacteria, such as bifidobacteria and lactobacilli, is necessary for the normal development of intestinal innate and adaptive immune defenses. The predominance of beneficial bacteria in the gut microflora of breast-fed infants is thought to be, at least in part, supported by the metabolism of the complex mixture of oligosaccharides present in human breast milk, and a more adult-type intestinal microbiota is found in formula-fed infants. Inadequate gut colonization, dysbiosis, may lead to an increased risk of infectious, allergic, and autoimmune disorders later in life. The addition of appropriate amounts of selected prebiotics to infant formulas can enhance the growth of bifidobacteria or lactobacilli in the colonic microbiota and, thereby, might produce beneficial effects. Among the substrates considered as prebiotics are the oligosaccharides inulin, fructo-oligosaccharides, galacto-oligosaccharides, and lactulose. There are some reports that such prebiotics have beneficial effects on various markers of health. For example, primary prevention trials in infants have provided promising data on prevention of infections and atopic dermatitis. Additional well-designed prospective clinical trials and mechanistic studies are needed to advance knowledge further in this promising field. (J Pediatr 2009;155:S61-70).

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Two experiments implement and evaluate a training scheme for learning to apply frequency formats to probability judgements couched in terms of percentages. Results indicate that both conditional and cumulative probability judgements can be improved in this manner, however the scheme is insufficient to promote any deeper understanding of the problem structure. In both experiments, training on one problem type only (either conditional or cumulative risk judgements) resulted in an inappropriate transfer of a learned method at test. The obstacles facing a frequency-based training programme for teaching appropriate use of probability data are discussed. Copyright (c) 2006 John Wiley & Sons, Ltd.

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A new Bayesian algorithm for retrieving surface rain rate from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) over the ocean is presented, along with validations against estimates from the TRMM Precipitation Radar (PR). The Bayesian approach offers a rigorous basis for optimally combining multichannel observations with prior knowledge. While other rain-rate algorithms have been published that are based at least partly on Bayesian reasoning, this is believed to be the first self-contained algorithm that fully exploits Bayes’s theorem to yield not just a single rain rate, but rather a continuous posterior probability distribution of rain rate. To advance the understanding of theoretical benefits of the Bayesian approach, sensitivity analyses have been conducted based on two synthetic datasets for which the “true” conditional and prior distribution are known. Results demonstrate that even when the prior and conditional likelihoods are specified perfectly, biased retrievals may occur at high rain rates. This bias is not the result of a defect of the Bayesian formalism, but rather represents the expected outcome when the physical constraint imposed by the radiometric observations is weak owing to saturation effects. It is also suggested that both the choice of the estimators and the prior information are crucial to the retrieval. In addition, the performance of the Bayesian algorithm herein is found to be comparable to that of other benchmark algorithms in real-world applications, while having the additional advantage of providing a complete continuous posterior probability distribution of surface rain rate.

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Analyzes the use of linear and neural network models for financial distress classification, with emphasis on the issues of input variable selection and model pruning. A data-driven method for selecting input variables (financial ratios, in this case) is proposed. A case study involving 60 British firms in the period 1997-2000 is used for illustration. It is shown that the use of the Optimal Brain Damage pruning technique can considerably improve the generalization ability of a neural model. Moreover, the set of financial ratios obtained with the proposed selection procedure is shown to be an appropriate alternative to the ratios usually employed by practitioners.

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This article proposes a new model for autoregressive conditional heteroscedasticity and kurtosis. Via a time-varying degrees of freedom parameter, the conditional variance and conditional kurtosis are permitted to evolve separately. The model uses only the standard Student’s t-density and consequently can be estimated simply using maximum likelihood. The method is applied to a set of four daily financial asset return series comprising U.S. and U.K. stocks and bonds, and significant evidence in favor of the presence of autoregressive conditional kurtosis is observed. Various extensions to the basic model are proposed, and we show that the response of kurtosis to good and bad news is not significantly asymmetric.

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Sting jets are transient mesoscale jets of air that descend from the tip of the cloud head towards the top of the boundary layer in severe extratropical cyclones and can lead to damaging surface wind gusts. This recently identified jet is distinct from the well-documented jets associated with the cold and warm conveyor belts. One mechanism proposed for their development is the release of conditional symmetric instability (CSI). Here the spatial distribution and temporal evolution of several CSI diagnostics in four severe storms are analysed. A sting jet has been identified in three of these storms; for comparison, we also analysed one storm that did not have a sting jet, even though it hadmany of the apparent features of sting-jet storms. The sting-jet storms are distinct from the non-sting-jet storms by having much greater andmore extensive conditional instability (CI) and CSI. CSI is released by ascending air parcels in the cloud head in two of the sting-jet storms and by descending air parcels in the other sting-jet storm. By contrast, only weak CI to ascending air parcels is present at the cloud-head tip in the non-sting-jet storm. CSI released by descending air parcels, as diagnosed by decaying downdraught slantwise convective available potential energy (DSCAPE), is collocated with the sting jets in all three sting-jet storms and has a localisedmaximum in two of them. Consistent evolutions of saturated moist potential vorticity are found.We conclude that CSI release has a role in the generation of the sting jet, that the sting jet may be driven by the release of instability to both ascending and descending parcels, and that DSCAPE could be used as a discriminating diagnostic for the sting jet based on these four case-studies.

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The regio- and stereoselective photoinduced addition of N-carbomethoxymethylpyrrolidine to 5(S)-tert-butyldimethylsiloxymethyl-furan-2(5H)-one in the presence of benzophenone yields 3(R)-[N-(diphenylhydroxymethyl)carbo methoxymethylpyrrolidin-2′-yl]-4(S)-tert-butyldimethylsiloxymethyl)-butan-4-olides (epimeric at C-2′), and we report the X-ray structure of the major adduct together with its conversion into the 1-azabicyclo[4.3.0]-nonane ring system.

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We consider the finite sample properties of model selection by information criteria in conditionally heteroscedastic models. Recent theoretical results show that certain popular criteria are consistent in that they will select the true model asymptotically with probability 1. To examine the empirical relevance of this property, Monte Carlo simulations are conducted for a set of non–nested data generating processes (DGPs) with the set of candidate models consisting of all types of model used as DGPs. In addition, not only is the best model considered but also those with similar values of the information criterion, called close competitors, thus forming a portfolio of eligible models. To supplement the simulations, the criteria are applied to a set of economic and financial series. In the simulations, the criteria are largely ineffective at identifying the correct model, either as best or a close competitor, the parsimonious GARCH(1, 1) model being preferred for most DGPs. In contrast, asymmetric models are generally selected to represent actual data. This leads to the conjecture that the properties of parameterizations of processes commonly used to model heteroscedastic data are more similar than may be imagined and that more attention needs to be paid to the behaviour of the standardized disturbances of such models, both in simulation exercises and in empirical modelling.